Application of ant colony optimisation algorithms in solving facility layout problems formulated as quadratic assignment problems: a review

Abstract

The formulation of Facility Layout Problems (FLPs) as Quadratic Assignment Problems (QAPs) has gained substantial attention from researchers. The main reason is that, QAPs provide possibilities to solve FLPs computationally. To date, there are two common approaches used to solve FLPs formulated as QAPs, that is, exact methods and approximate methods (also known as heuristics). In recent years, there is an increasing interest in solving QAPs using the general extension of heuristic methods called metaheuristics. Ant Colony Optimisation (ACO) has currently emerged as a new and promising metaheuristic. This paper is aimed to provide a comprehensive review of the concepts of ACO and its application in solving QAPs. In addition, the various ACO algorithms or variants developed to solve them are critically analysed and discussed. It is shown that these existing algorithms still possess many limitations and weaknesses. Finally, useful strategies and research directions are provided to improve these weaknesses.